Content delivery monitor

ABSTRACT

Technologies are generally described for systems and methods to identify defective segments of content data. The methods may comprise generating a monitor agent effective to generate a request for the content data. The methods may comprise deploying the monitor agent to an address. The monitor agent may be effective to extract the content data and to generate delivery data associated with the content data. The methods may comprise distributing the delivery data to a parameter processor. The methods may comprise generating parameter data. The parameter data may be effective to indicate a parameter level associated with a parameter of the content data. The methods may comprise generating performance data based on the parameter data. The performance data may be effective to indicate a number of defects among the content data. The methods may comprise identifying a number of defective segments among the content data based on the performance data.

BACKGROUND OF THE INVENTION

Unless otherwise indicated herein, the materials described in thissection are not prior art to the claims in this application and are notadmitted to be prior art by inclusion in this section.

Owners of content, such as live streaming events and/or videos, mayemploy a content delivery network to distribute the content to users whowish to view the content. In some examples, the content delivery networkmay distribute content data associated with the content over a network.Users may use devices such as computers or mobile devices, which may beconnected to the network, to receive the content data in order to viewthe content.

SUMMARY OF THE INVENTION

In some examples, methods effective to identify defective segments ofcontent data associated with a piece of content are generally described.The methods may comprise an agent generator of a monitor domaingenerating a monitor agent. The monitoring agent may be effective togenerate a first request from a first address. The first request may befor the content data. The first request may be a simulation of a secondrequest from a second address in a user domain. The methods may comprisea monitor processor of the monitor domain deploying the monitor agent tothe first address. The monitor agent may be effective to extract thecontent data from a content delivery domain to the first address. Themonitor agent may be effective to generate delivery data associated withthe content data. The delivery data may include data associated with adelivery of the content data from the content delivery domain to themonitor agent at the first address. The methods may comprise acontroller of the monitor domain receiving the delivery data from themonitor agent. The methods may comprise the controller distributing thedelivery data to a parameter processor of the monitor domain. Themethods may comprise the parameter processor generating parameter data.The parameter data may be effective to indicate a parameter levelassociated with a parameter of the content data. The methods maycomprise a monitoring processor of the monitor domain generatingperformance data based on the parameter data. The performance data maybe effective to indicate a number of defects among the content data. Themethods may comprise an analytical data generator of the monitor domainidentifying a number of defective segments among the content data basedon the performance data. In some examples, systems effective to identifydefective segments of content data associated with a piece of contentare generally described. The systems may comprise a memory. The systemsmay comprise an agent generator configured to be in communication withthe memory. The systems may comprise a monitor processor configured tobe in communication with the agent generator and the memory. The systemsmay comprise a controller configured to be in communication with themonitor processor. The systems may comprise a parameter processorconfigured to be in communication with the controller and the monitorprocessor. The systems may comprise an analytical data generatorconfigured to be in communication with the monitor processor. The agentgenerator may be configured to generate a monitor agent that iseffective to generate a first request from a first address. The firstrequest may be for the content data. The first request may be asimulation of a second request from a second address in a user domain.The monitor processor may be configured to deploy the monitor agent tothe first address. The monitor agent may be effective to extract thecontent data from a content delivery domain. The monitor agent may beeffective to generate delivery data associated with the content data.The delivery data may include data associated with a delivery of thecontent data from the content delivery domain to the monitor agent atthe first address. The controller may be configured to receive thedelivery data from the monitor agent and distribute the delivery data tothe parameter processor. The parameter processor may be configured togenerate parameter data. The parameter data may be effective to indicatea parameter level associated with a parameter of the content data. Theparameter processor may be configured to send the parameter data to themonitor processor. The monitor processor may be further configured togenerate performance data based on the parameter data. The performancedata may be effective to indicate a number of defects among the contentdata. The monitor processor may be configured to send the performancedata to the analytical data generator. The analytical data generator maybe configured to, based on the performance data, identify a number ofdefective segments among the content data.

In some examples, systems effective to evaluate a delivery of contentdata from a content delivery domain to a user domain are generallydescribed. The systems may comprise a memory configured to store thecontent data. The systems may comprise a content provider processorconfigured to be in communication with the memory. The content providerprocessor may be configured to distribute a copy of the content data toa content delivery domain. The systems may comprise an agent generatorconfigured to be in communication with the memory. The systems maycomprise a monitor processor configured to be in communication with theagent generator and the memory. The systems may comprise a controllerconfigured to be in communication with the monitor processor. Thesystems may comprise a parameter processor configured to be incommunication with the controller and the monitor processor. The systemsmay comprise an analytical data generator configured to be incommunication with the monitor processor. The agent generator may beconfigured to generate a monitor agent that is effective to generate afirst request from a first address. The first address may be for thecontent data distributed to the content delivery domain. The firstrequest may be a simulation of a second request a second address in auser domain. The monitor processor may be configured to deploy themonitor agent to a second address. The monitor agent may be effective toextract the content data from the content delivery domain. The monitoragent may be effective to generate delivery data associated with thecontent data distributed from the content delivery domain. The deliverydata may include data associated with a delivery of the content datafrom the content delivery domain to the monitor agent at the firstaddress. The controller may be configured to receive the delivery datafrom the monitor agent and distribute the delivery data to the parameterprocessor. The parameter processor may be configured to generateparameter data. The parameter data may be effective to indicate aparameter level associated with a parameter of the content data. Theparameter processor may be configured to send the parameter data to themonitor processor. The monitor processor may be further configured togenerate performance data based on the parameter data. The performancedata may be effective to indicate a number of defects among the contentdata. The monitor processor may be configured to send the performancedata to the analytical data generator. The analytical data generator maybe configured to, based on the performance data, identify a number ofdefective segments among the content data. A presence of defectivesegments among content data may be effective to indicate an efficiencyof the delivery of the content data from the content delivery domain tothe user domain. The analytical data generator may be configured togenerate analytical data based on the performance data. The analyticaldata may be effective to indicate the identified defective segmentsamong the content data. The analytical data generator may be configuredto evaluate the delivery of the content data from the content deliverydomain to the user domain based on the analytical data.

BRIEF DESCRIPTION OF THE FIGURES

The foregoing and other features of this disclosure will become morefully apparent from the following description and appended claims, takenin conjunction with the accompanying drawings. Understanding that thesedrawings depict only several embodiments in accordance with thedisclosure and are, therefore, not to be considered limiting of itsscope, the disclosure will be described with additional specificity anddetail through use of the accompanying drawings, in which:

FIG. 1 illustrates a drawing of an example system to implement a contentdelivery monitor;

FIG. 2 illustrates the example system of FIG. 1 with additional detailsrelating to an implementation of a content delivery monitor;

FIG. 3 illustrates the example system of FIG. 1 with additional detailsrelating to an implementation of a content delivery monitor;

FIG. 4 illustrates a flow diagram for an example process to implement acontent delivery monitor;

all arranged according to at least some embodiments described herein.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT(S)

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented herein. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe Figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein.

FIG. 1 illustrates a drawing of an example system to implement a contentdistribution monitor, arranged in accordance with at least someembodiments described herein. An example system 100 may include aninfrastructure 102, a content delivery domain 120, a content providerdomain 130, and/or a monitor domain 140. Infrastructure 102, contentdelivery domain 120, content provider domain 130, and/or monitor domain140 may be configured to be in communication with each other through anetwork such as the Internet, WI-FI, a local area network, a wide areanetwork, a cellular network, etc. In some examples, infrastructure 102may be a cloud computing platform including one or more resources 105(e.g., AMAZON WEB SERVICES), where resources 105 may include hardwareresources such as processors, memories, servers (such as a cloud server107 and a cloud memory 108), etc. Infrastructure may be located at alocation that corresponds to an address 103 (e.g., an Internet Protocol(IP) address).

Content provider domain 130 may include a system that may be used by acontent provider 131, where content provider 131 may be an entity (e.g.,a company) that provides content to one or more users. Content provider131 may also include a content distributor that distributes content toone or more users. In some examples, content provider 130 may providecontent to users that may be subscribed to, or registered with, contentprovider 131. Content provided by content provider 131 may includevideos such as movies, television shows, etc. Content provider domain130 may include one or more pieces of hardware components, such as acontent provider processor 132 and/or a content provider memory 134,configured to be in communication with each other. Content providermemory 134 may be configured to store one or more pieces of content dataassociated with corresponding content. For example, content providermemory 134 may store content data 104 that may be associated withcontent 106. Content data 104, when processed or rendered by a device(e.g., a user device 114), may be outputted as content 106. Contentprovider domain 130 may distribute one or more copies of content data104 to one or more servers among content delivery domain 120 in orderfor content delivery domain 120 to distribute content data 104 to one ormore user devices.

Content provider domain 130 may utilize resources 105 amonginfrastructure 102 to facilitate content distribution to userssubscribed with content provider 131. In examples where infrastructure102 may be a cloud computing platform, content provider 131 may pay thecloud computing platform for usage of resources 105 to execute adistribution instruction 136, where distribution instruction 136includes instructions associated with distribution of content to userdevices. For example, upon paying for usage of resources 105, contentprovider 131 may utilize cloud memory 108 to store distributioninstruction 136, and may utilize cloud server 107 to executedistribution instruction 136.

Content delivery domain 120 may include one or more content deliveryservers 121 (including 121 a, 121 b, 121 c, 121 d). Each contentdelivery server may be located in a respective location, such as ageographical region. Cloud server 107 may execute distributioninstruction 136 to identify a content delivery server. Identification ofa content delivery server may be based on one or more protocols relatingto location, latency, bandwidth, content sharing, region, connectionspeed, etc. For example, cloud server 107 may identify a contentdelivery server that may be located in proximity, or closest, to userdevice 114. In the example shown in FIG. 1, content delivery server 121d may be located geographically closest to user device 114 when comparedto locations of content delivery servers 121 a, 121 b, 121 c. Eachcontent delivery server 121 may include a respective processor, andrespective memory configured to store respective set of content data.Focusing on content delivery server 121 d, content delivery server 121 dmay include a content delivery processor 122 d and a content deliverymemory 124 d, where content delivery memory 124 d may store content data104 that was received from content provider domain 130.

In an example, a user domain 110 may be configured to be incommunication with content delivery domain 120. User domain 110 mayinclude user device 114, where user device 114 may be used, orcontrolled, by a user 112. User device 114 may be configured to executean application 116, where application 116 may be an applicationassociated with content provider 131. For example, content provider 131may be HBO, or, NETFLIX, etc., and application 116 may be an applicationexecutable by user device 114 to output content data, or to facilitateplayback of content, provided by content provider 131. User 112 maycontrol user device 114 to generate a user input 118 by use ofapplication 116. For example, a user interface of application 116 mayallow user 112 to select a particular piece of content, a playbackquality of the particular piece of content, etc. User device 114 maysend user input 118 to cloud server 107 among infrastructure 102, whereuser input 118 may include indications of a request for the particularpiece of content, such as content 106.

Cloud server 107 may execute distribution instruction 136 to processuser input 118, such as authenticating user device 114, identifying anindication of content 106 among user input 118, identifying an address113 (e.g., an IP address) of user device 114, etc. Cloud server 107 mayexecute distribution instruction 136 to generate a retrieval instruction119, where retrieval instruction 119 may include instructions effectiveto command content delivery domain 120 to send content data 104(associated with content 106) to user device 114. For example, retrievalinstruction 119 may include an instruction effective to command contentdelivery domain 120 to send content data 104 to user device 114 ataddress 113. As a result, user device 114 may receive content data 104from content delivery domain 120 and may output content data 104 ascontent 106 in application 116. In some examples, an output of contentdata 104 may include rendering content data 104 in order for contentdata 104 to be output as content 106.

Monitor domain 140 may include a system comprising one or more pieces ofhardware components configured to facilitate generation of analyticaldata 162, where analytical data 162 may include data effective toindicate one or more portions of content data 104. In some examples, theone or more portions of content data indicated by analytical data 162may be detected portions of content data 104. In the example shown inFIG. 1, monitor domain 140 may include, at least, a monitor processor142, a monitor memory 144, and an analytical data generator 150. Monitorprocessor 142, monitor memory 144, and analytical data generator 150 maybe configured to be in communication with each other. In some examples,monitor processor 142 may be configured to control operations ofanalytical data generator 150 and other hardware components, such asspecial purpose processors, of monitor domain 140. Monitor memory 144may be configured to store a monitor instruction 161, where monitorinstruction 161 may include instructions effective to facilitategeneration of one or more monitor agent(s) 152 (described below) andanalytical data 162 (described below). In some examples, the system ofmonitor domain 140 may be a part of content provider domain 130, asshown by the dotted lines around monitor domain 140.

As will be further described below, monitor domain 140 may generate oneor more monitor agent(s) 152. Monitor domain 140 may deploy monitoragent 152 to address 103 of infrastructure 102, where monitor agent 152may include instructions, and resources 105 may execute instructionsincluded in monitor agent 152 to perform one or more operations. Forexample, resources 105 may execute monitor agent 152 to facilitateextraction of content data 104 from content delivery domain 120. In someexamples, monitor agent 152 may include instructions effective tosimulate operations of one or more user devices in user domain 110.Examples of simulation may include performing operations (e.g.,generation of data, requests, execution of instructions, etc.) based ona particular hardware, software, firmware, etc., of the one or more userdevices in user domain 110. For example, resources 105 may executemonitor agent 152 to generate a content data request 154, where contentdata request 154 may include indications of a particular version of anoperating system of user device 114, indications of address 113, orindications of other information related to user device 114, in order tosimulate a request for content data 104 from user device 114. Monitoragent 152 may send content data request 154 to content delivery server121 d in order to request content data 104. Content delivery server 121d may receive content data request 154 and, in response, may sendcontent data 104 to monitor agent 152. In some examples, resources 105may execute instructions in monitor agent 152 to extract, or pull,content data 104 from content delivery domain 120. In examples wheremonitor agent 152 extract content data 104 from content delivery domain120, content data request 154 may include an authentication request forcontent delivery server 121 d to authenticate monitor agent 152. Forexample, content data request 154 may include indications of credentialsassociated with monitor agent 152. Content delivery server 121 d mayanalyze the credentials included in content data request 154 and, upon adetermination that the credentials are valid, may authorize monitoragent 152 to extract content data 104 from content delivery server 121d. In another example, content data request 154 may include apre-authenticated token or equivalent mechanism provingauthentication/authorization from an earlier request to a separatesystem owned by content delivery domain 120 or content provider domain130. Content delivery server 121 d may analyze the a pre-authenticatedtoken or equivalent mechanism included in content data request 154 and,upon a determination that the a pre-authenticated token or equivalentmechanism is valid, may authorize monitor agent 152 to extract contentdata 104 from content delivery server 121 d.

Monitor agent 152 may extract content data 104 from content deliverydomain 120 and, in response, may generate delivery data 155, wheredelivery data 155 may include at least a portion of content data 104,and may include additional data relating to content data 104 (theadditional data will be described below). Monitor agent 152 may senddelivery data 155 to monitor domain 140. Monitor domain 140 may receivedelivery data 155 and, in response, may generate performance data 156based on delivery data 155. In some examples, monitor processor 142 maygenerate performance data 156, or may control one or more specialpurpose processors (further described below) among monitor domain 140 togenerate performance data 156. In some examples, performance data 156may include data effective to indicate whether a number of parameterdefects (further described below) among content data 104. In someexamples, performance data 156 may include data effective to indicateparameter levels associated with one or more parameters of an output ofcontent data 104 (further described below). In some examples,performance data 156 may be based on a delivery of content data 104 fromcontent delivery domain 120 to monitor agent 152. In some examples,performance data 156 may be associated with a performance of a deliveryand/or an output of content data 104. For example, performance data 156may include data effective to indicate a level of defect of an audioquality of content 106. A level of defect of the audio quality may beaffected by factors such as latency, bandwidth availability,interference, noise, etc. The level of defect of the audio quality maybe affected during the transmission of content data 104 from contentdelivery domain 120 to monitor agent 152 or during the original receipt,encoding, packaging or other preparatory steps of content deliverydomain 120 obtaining content data 104 from content provider domain 130.

Monitor processor 142 may send performance data 156 to analytical datagenerator 150. Analytical data generator 150 may generate analyticaldata 162 based on performance data 156 and, in response, may sendanalytical data 162 to content provider domain 130. In some examples,analytical data 162 may include data effective to indicate one or moredefected portions of content data 104. In some examples, analytical data162 may further include data effective to indicate one or morerecommendations associated with storage and/or delivery of content data104 (further described below). Analytical data generator 150 may sendanalytical data 162 to content provider domain 130. Content provider 131may use analytical data 162, received at content provider domain 130, toevaluate a delivery of content data 104. For example, content provider121 may use analytical data 162 to determine whether to makeadjustments, such as altering hardware resources, storage location ofcontent data 104, etc., based on analytical data 162. In anotherexample, agent 164 of content provider domain 130 may use analyticaldata 162 to determine whether to make adjustments based on analyticaldata 162.

FIG. 2 illustrates the example system of FIG. 1 with additional detailsrelating to an implementation of a content distribution monitor,arranged in accordance with at least some embodiments described herein.The example system in FIG. 2 could be implemented as, for example,system 100 discussed above. Those components in FIG. 2 that are labelledidentically to components of FIG. 1 will not be described again for thepurposes of clarity.

As will be described in more detail below, monitor domain 140 mayinclude one or more parameter processors 220 (including 220 a, 220 b,220 c). Each parameter processor 220 may be configured to generate arespective set of parameter data 222 (including 222 a, 222 b, 222 c).Each set of parameter data 222 may correspond to a particular parameterassociated with content data 104, and may include data effective toindicate a parameter level of the corresponding parameter. In someexamples, parameter data 222 may correspond to one or more segments ofcontent data 104. Parameters may include receipt time, authenticity,blurriness, black screen, frozen screen, macroblocking, pixilation,framerate loss, audio availability, audio quality, data loss, etc.Monitor processor 142 may generate performance data 156 based onparameter data 222.

In an example, content data 104 may be partitioned into one or moresegments 200 (including 200 a, 200 b, 200 c). Each segment 200 may be achunk, or a piece of data, that corresponds to a portion of content 106.For example, content 106 may be a video of a length of sixty minutes,and content data 104 may be partitioned into ten segments such that eachsegment may correspond to six minutes of the video. In some examples,segments 200 may be of same or different sizes (e.g., number of bytes),where a size of a segment may be based on content 106. In some examples,segments 200 may be arranged in a particular order, and the particularorder may be indicated by manifest files and/or metadata associated withrespective segments (further described below).

Monitor agent generator 150 may generate monitor agent 152 based onmonitor instruction 161 stored in monitor memory 144. Monitorinstruction 161 may include instructions for monitor agent generator 150to generate monitor agents based on, one or more of, a model of a userdevice, a firmware version of a user device, an operating system of auser device, a content retrieval protocol, one or more locations ofinfrastructure 102, one or more locations of content delivery servers121, etc.

In an example, content provider 131 may use monitor domain 140 togenerate monitor agent 152 to simulate an IPHONE running on a particularversion of an operating system (e.g., iOS 10.3.2) configured to retrievecontent data 104 based on the Hypertext Transfer Protocol Live Streaming(HLS) protocol. Monitor agent generator 150 may retrieve portions ofmonitor instruction 161 that corresponds to IPHONE, the particularversion of the operating system, and the HLS protocol, to generatemonitor agent 152. In some examples, content provider 131 may alsospecify a particular infrastructure to deploy monitor agent 152. Forexample, content provider 131 may request to deploy monitor agent 152 toinfrastructure 102. In some examples, content provider 131 may requestto monitor content delivery performance of a particular geographicalregion. Monitor domain 140 may identify one or more content deliveryservers 121 located within the particular geographical region and, inresponse, select the infrastructure to deploy monitor agent 152. In someexamples, associations indicating locations of content delivery servers121 with respect to one or more infrastructures may be stored in monitormemory 144. Monitor domain 140, or monitor processor 142, may identifycontent delivery servers 121 among the stored associations in order toidentify an infrastructure to deploy monitor agent 152.

Monitor agent 152 may include instructions, or code, effective tosimulate one or more operations of a user device as indicated by therequest from content provider 131. For example, monitor agent 152 maysimulate an IPHONE and retrieve content data 104 based on the HLSprotocol. Monitor agent 152 may simulate one or more operations of auser device based on a specific version of a user device, an operatingsystem of the user device, a client-player of the user device, specificprotocols of the user device, etc. Further, monitor agent may generatetimestamps 201 (including 201 a, 201 b, 201 c) for each segmentextracted from content delivery server 121 d, where each timestamp 201may indicate a receipt time of a corresponding segment received atmonitor agent 152. Monitor agent 152 may combine the extracted segmentswith corresponding generated timestamps to generate delivery data 155.

Monitor agent 152 may send delivery data 155 to a memory 202. In someexamples, memory 202 may be a cache memory. Memory 202 may be a memoryunit configured to store delivery data 155. Memory 202 may include amemory controller 205, where memory controller 205 may be configured tofacilitate receipt, transmission, and distribution, of delivery data 155to parameter processors 220.

Parameter processors 220 may each be configured to determine parameterlevels associated with parameters of an output of one or more segments200 of content data 104. For example, parameter processor 220 a may beconfigured to determine a level of blurriness of one or more segments200 of content data 104. Parameter processor 220 b may be configured todetermine a level of pixelation of one or more segments 200 of contentdata 104. For example, parameter processor 220 b may identify a portionof segment 200 c, where the portion includes unwanted pixels. Parameterprocessor 220 b may further determine a percentage that reflects a ratioof a size (e.g., file size) of the identified portion relative to a sizeof segment 200 c. Parameter processor 220 c may be configured todetermine whether segments 200 are received at monitor agent 152 atappropriate receipt times. Each parameter processor 220 may beconfigured to perform respective analysis and generate respectiveparameter data 222. For example, a parameter processor 220 that may beconfigured to perform audio analysis may be configured to compare closedcaptioning of an output of content data 104 with subtitle filesassociated with content 106 that may be stored in monitor memory 144.

In an example, monitor agent 152 may be a data availability agent suchthat monitor agent 152 may be configured to detect an availability ofsegments 200 at content delivery server 121 d. In response to adetection that segments 200 are available at content delivery server 121d, monitor agent 152 may extract the available segments 200 from contentdelivery server 121 d. For example, in response to a detection thatsegments 200 a, 200 b are available at content delivery server 121 d,monitor agent 152 may extract segments 200 a, 200 b from contentdelivery server 121 d and subsequently, wait for an availability ofsegment 200 c. After waiting for a period of time, monitor agent 152 maydetermine that segment 200 c is available at content delivery server 121d and, in response, may extract segment 200 c from content deliveryserver 121 d.

Monitor agent 152 may receive segments 200 a, 200 b, 200 c of contentdata 104 at respective times and, in response, may generate timestamps201 a, 201 b, 201 c to indicate the respective times. Monitor agent 152may generate delivery data 155 by compiling the received segments 200 a,200 b, 200 c with corresponding timestamps 201 a, 201 b, 201 c. In someexamples, monitor agent 152 may further extract metadata and/or manifestdata (e.g., manifest files) of content data 104 from content deliveryserver 121 d. In some examples, delivery data 155 may further includemanifest files and/or metadata that may be effective to describe eachsegment 200.

Monitor agent 152 may send delivery data 155 to memory 202. Memorycontroller 205 of memory 202 may distribute at least a portion ofdelivery data 155 to one or more parameter processors 220. In theexample shown in FIG. 2, memory controller 205 may send delivery data155 to parameter processors 220 a, 202 b, 220 c. Each parameterprocessor 220 may receive delivery data 155 and, in response, mayidentify respective portions of delivery data 155 in order to generaterespective parameter data 222.

In an example, parameter processor 220 a may be configured to determinea level of blurriness of content 106. Parameter processor 220 a mayidentify content data 104 among delivery data 155 and, in response, maydetermine parameter data 222 a. Parameter processor 220 a may not needto process timestamps 201 as timestamp 201 may be irrelevant to adetermination of blurriness of content 106. Parameter processor 220 amay be configured to process a playback of content 106 in order toanalyze video frames among each segment 200 of content data 104.Parameter processor 220 a may generate parameter data 222 a based on theanalysis of content data 104, where parameter data 222 a may includedata effective to indicate a level of blurriness of one or more segments200 of content data 104. In some examples, parameter 222 a may indicatewhether each segment 222 exceeds a particular level of blurriness.

For example, parameter processor 220 a may apply instructions relatingto image processing techniques such as Laplace filters, Fast FourierTransform, etc., on segments 200 to determine a level of blurriness foreach segment 200. Parameter processor 220 a may compare each determinedlevel of blurriness to a blurriness threshold 230, where blurrinessthreshold 230 may be assigned and/or adjusted by content provider 131.For example, parameter data 222 a may compile results of comparisonsbetween each determined level of blurriness with blurriness threshold230 in order to generate parameter data 222 a. In the example shown inFIG. 2, parameter data 222 a may include data effective to indicatewhether each segment 200 may be blurry or not blurry (where, in FIG. 2,an indication of blurry is represented by a shaded box in parameter data222 a). Parameter processor 220 a may send parameter data 222 a tomonitor processor 142.

In some examples, a value of blurriness threshold 230 may be based on aparticular compression technique. For example, if content data 104 iscompressed based on the H264 compression codec prior to a transmissionof content data 104 from content delivery server 121 d to monitor agent152, a value of blurriness threshold 230 may be based on the H264compression codec. In some examples, blurriness threshold 230 may bestored in a component, such as a register, of parameter processor 220 a.

Continuing with the example shown in FIG. 2, parameter processor 220 bmay be configured to determine a level of pixelation of each segment200. For example, parameter processor 220 b may apply image processingtechniques such as edge detection to determine a level of pixilation ofeach segment 200. Parameter processor 220 b may generate parameter data222 b that may include data effective to indicate a level of pixilationof each segment 200. In some examples, parameter data 222 b may indicatewhether each segment 200 exceeds a particular level of pixilation.Parameter processor 220 b may send parameter data 222 b to monitorprocessor 142.

Continuing with the example shown in FIG. 2, parameter processor 220 cmay be configured to determine an timeliness of receipt times ofsegments 200 at monitor agent 152. For example, parameter processor 220c may include a storage component, such as one or more registers,configured to store protocol data 240. Protocol data 240 may includedata effective to indicate receipt times of chunks, or segments 200, ofcontent 104 based on a particular retrieval protocol. For example, ifmonitor agent 152 is configured to retrieve segments 200 based on theHLS protocol, protocol data 240 may include data effective to indicatereceipt time of segments 200 based on the HLS protocol. Parameterprocessor 220 c may compare timestamps 201 with receipt times indicatedby protocol data 140 and, in response, may identify segments 200 thatmay correspond to timestamps 201 that may be significantly differentfrom the receipt times indicated by protocol data 240. For example,protocol data 240 may further include data effective to indicate areceipt time threshold. Parameter processor 220 c may determinedifferences between timestamps 201 and receipt times indicated byprotocol data 240. Parameter processor 220 c may compare the determineddifferences with the receipt time threshold in order to identify whethereach segment 200 is received at monitor agent 152 at an appropriatereceiving time. If a determined difference is greater than the receipttime threshold, then a discrepancy in receiving time is present and thecorresponding segment may be marked as being received at an incorrectreceipt time (where, in FIG. 2, an indication of an incorrect receipttime is represented by a shaded box in parameter data 222 c). Inresponse to the comparison, parameter processor 220 c may generateparameter data 222 c, where parameter data 222 c may include dataeffective to indicate whether each segment 200 is received at a correct,or incorrect, receipt time. Parameter processor 220 c may send parameterdata 222 c to monitor processor 142.

Monitor processor 142 may receive parameter data 222 a, 222 b, 222 cand, in response, may generate performance data 156 based on parameterdata 222 a, 222 b, 222 c. In some examples, monitor processor 142 maystore parameter data 222 a, 222 b, 222 c, in monitor memory 144. In someexamples, monitor processor 142 may update database 204, stored inmonitor memory 144, based on parameter data 222 a, 222 b, 222 c.Database 204 may be effective to indicate parameter data associated withone or more pieces of content, one or more monitor agents, etc. Forexample, database 204 may include entries effective to indicatecorrespondence among content 106, monitor agent 152, and receipt timesof content data 104 at monitor agent 152. Database 204 may furtherinclude entries effective to indicate parameter data associated witheach instance of collection of content data 104 at each monitor agent.For example, database 204 may indicate associations between content data104 (associated with content 106), monitor agent 152, and timestamps 201in order to indicate that content data 104 was collected by monitoragent 152 at a set of times corresponding to respective timestamps 201.Database 204 may further indicate associations between parameter data222, segments 200, and timestamps 201 in order to indicate thatparameter data 222 corresponds to segments 200 that were collected attimestamps 201.

Historical data processor 172 may access data among database 204 tofacilitate generation of performance data 156. For example, monitorprocessor 142 may receive parameter data 222 and, in response, mayrequest historical data processor 172 to retrieve one or more portionsof data among database 204. In some examples, monitor processor 142 mayspecify the one or more portions of database 204 to be retrieved byhistorical data processor 172. For example, monitor processor 142 mayrequest historical data processor 172 to retrieve a portion of database204 that corresponds to, at least one of, one or more particular dates(dates may be indicated by timestamps), one or more monitor agents, oneor more particular parameter, etc.

In some examples, database 204 may further indicate a history ofdeployment locations of one or more monitor agents. For example,database 204 may indicate monitor agent 152 was deployed toinfrastructure 102 in the past week. Monitor processor 142 may furtherrequest historical data processor 172 to retrieve a portion of database204 that corresponds to one or more infrastructures.

In some examples, database 204 may further indicate associations betweenmonitor agents and one or more content delivery servers, in order toindicate the content delivery servers where data was extracted by one ormore monitor agents. For example, database 204 may indicate monitoragent 152 has been collecting delivery data 155 from content deliveryserver 121 d in the past week. Monitor processor 142 may further requesthistorical data processor 172 to retrieve data associated with a portionof database 204 that corresponds to one or more content deliveryservers.

In some examples, parameter processors 220 may each be low power devicessuch that each parameter processor 220 may be configured to generateparameter data 222 associated with some particular parameters whilelacking hardware and/or functionality to generate parameter data 222 forother parameters. For example, parameter processors 200 may lack graphicprocessing units to render, or output, segments 200, but may includesufficient hardware to compare receipt times of segments 200. In someexamples, parameter processors 220 that may be low power devices may beconfigured to perform individual frame analysis such as determination ofpixelation or blurriness. In some example, when parameter processors 220are low power devices, parameter processors may lack the hardware and/orfunctionality to perform cross frame analysis such as determination offramerate loss.

In examples where each parameter processor 220 may be a low powerdevice, monitor domain 140 may further include a content controller 250and a production processor 260. Content controller 250 may be configuredto be in communication with memory 202, memory controller 205, andparameter processors 220. Production processor 260 may be configured tobe in communication with monitor processor 142 and monitor memory 144.

Content controller 250 may be configured to control, or manage,distribution of segments 200 from memory 202 to parameter processors200. In an example, content controller 250 may distribute segments 200such that segment 200 a is sent to parameter processor 220 a, segment200 b is sent to parameter processor 220 b, and segment 200 c is sent toparameter processor 220 c. In some examples, parameter processors 220may determine parameter data 222 for segments 200 a, 200 b, 200 c, inparallel. In other examples, content controller 250 may be configured todetermine availability of one or more parameter processors 220 such thatsegments 200 may be distributed to parameter processors 220 that may beactive or available.

Production processor 260 may be configured to determine parameter data(e.g., parameter data 222 d) that may be associated with relativelycomplex analysis of content data 104. For example, when parameterprocessors 220 a, 220 b, 220 c are each low power devices, productionprocessor 260 may be configured to determine parameter data that may notbe determined by parameter processors 220 a, 220 b, 220 c based onparameter processors 220 a, 220 b, 220 c being low power devices. Forexample, production processor 250 may be configured to performrelatively complex analysis, such as cross frame analysis, on contentdata 104.

In some examples, a copy of content data 104 may be stored in monitormemory 144. Parameter processors 220 and/or production processor 260 maycompare an output of content data 104 that is stored in monitor memory144 with an output of segments 200 included in delivery data 155 toidentify defects of segments 200. In some examples, parameter processor220 may hash content data 104 stored in monitor memory 144, and may hashsegments 200 include in delivery data 155, and compare the hashes todetermine if data was lost during the transmission of segments 200 fromcontent delivery server 121 d to monitor agent 152.

In some examples, monitor memory 144 may store metadata associated withcontent data 104. For example, monitor memory 144 may store manifestfiles associated with content data 104, where the manifest files may beeffective to describe segments 200 among content data 104. Parameterprocessors 220 may compare metadata of content data 104 stored inmonitor memory 144 with metadata included in delivery data 155 in orderto determine whether segments 200 received by monitor agent 152 areidentical to content data 104 stored in monitor memory 104. In someexamples, parameter processors 220 may compare the stored manifest fileswith manifest files included in delivery data 155 to determine whethersegments 200 received by monitor agent 152 are identical to content data104 stored in monitor memory 104. In some examples, parameter processors220 may compare hashes of metadata or manifest files stored in monitormemory 144, with hashes of metadata of manifest files included indelivery data 155, to determine an authenticity of segments 200 receivedby monitor agent 152.

Monitor processor 142 may generate performance data 156 based onparameter data 222, data retrieved by historical data processor 172,and/or parameter data 222 d generated by production processor 250.Performance data 156 may include data effective to indicate aperformance of a delivery and/or an output of content data 104. As willbe described in more detail below, performance data 156 may include dataeffective to indicate whether one or more segments 200 are defective,and how many defected parameters are present among each segment 200.

FIG. 3 illustrates the example system of FIG. 1 with additional detailsrelating to an implementation of a content distribution monitor,arranged in accordance with at least some embodiments described herein.The example system in FIG. 3 could be implemented as, for example,system 100 discussed above. Those components in FIG. 3 that are labelledidentically to components of FIGS. 1-2 will not be described again forthe purposes of clarity.

Monitor processor 142 may generate performance data 156 based onparameter data 222 and/or data in database 204. In an example shown inFIG. 3, monitor processor 142 may determine, for each segment 200, anumber of defects present in the corresponding segment. For example,monitor processor 142 may determine that segment 200 a includes zero(‘0’) defects, segment 200 b includes one (‘1’) defect, and segment 200c includes three (‘3’) defects. Monitor processor 142 may generateperformance data 156 based on the determined number of defects for eachsegment 200. Monitor processor 142 may generate performance data 156such that performance data 156 may include indications of the number ofdefects for each segment 200. In the example shown in FIG. 3,performance data 156 may indicate that segment 200 a includes zerodefects, segment 200 b includes one defect, and segment 200 c includesthree defects. Monitor processor 142 may send performance data 156 toanalytical data generator 160.

Analytical data generator 160 may analyze performance data 156 todetermine a presence of one or more segments, among content data 104,that may be defective. For example, monitor instruction 161 may includea segment defect threshold 302, where segment defect threshold 302 mayinclude an indication of a number of defects that may be used byanalytical data generator 160 to categorize a segment as defective.Defective threshold 250 may indicate two defects, such that a segmentthat includes two or more defects may be categorized as defective, and asegment that includes less than two defects may be categorized as notdefective. In response to a particular segment being categorized asdefective, analytical data generator 160 may determine that there is apresence of a defected portion (e.g., the particular segment) amongcontent data 104.

In some examples, a presence and/or an absence of one or more defectivesegments among content data 104 may indicate an efficiency of a deliveryof content data 104 from content delivery domain 120 to user domain 110.For example, an absence of defective portions among content data 104 mayindicate an efficient delivery of content data 104, whereas a presenceof defective portions among content data may indicate an inefficientdeliver of content data 104.

In the example shown in FIG. 3, analytical data generator 160 maygenerate analytical data 162 based on performance data 156 and defectivethreshold 302. For example, Analytical data generator 160 may compareeach number of defects, of each segment 200, among performance data 156with segment defect threshold 302 and, in response, may identifysegments 200 that may be categorized as defective. In the example,segments 200 a, 200 b may be categorized as not defective, and segment200 c may be categorized as defective.

Analytical data generator 160 may generate analytical data 162 based onthe identification of segments 200 as defective or not defective. Forexample, analytical data generator 160 may generate analytical data 162that may indicate among segments 200, there is one defective segment,and/or thirty-three percent (two out of three) of segments aredefective. Analytical data 162 may further include an identification ofthe defective segments, and the associated defects of the defectedsegment. In some examples, analytical data 162 may be output, such as bycontent provider domain 130, as a report that may include indications ofdefected segments.

Analytical data generator 160 may send analytical data 162 to contentprovider domain 130. Content provider domain 130 may use analytical data162 to evaluate a delivery of content data 104 from content deliverydomain 120 to user domain 110. For example, analytical data 162 may beused to evaluate a delivery of content data 104 from content deliveryserver 121 d to user device 114, where user device 114 may requestcontent data 104 from content delivery domain 120 using infrastructure102. In some examples, content provider domain 130 may use analyticaldata 162 to determine whether adjustments to storage locations, storagemethods, content retrieval protocols, etc., of content data 104 arenecessary. In some examples, content provider domain 130 may useanalytical data 162 to determine whether hardware at particular contentdelivery domains are performing at an acceptable level. In someexamples, in response to segment 200 c being identified by analyticaldata 162, content provider domain 130 may determine to replace segment200 c stored in content delivery server 121 d with a new copy of segment200 c. In some examples, in response to segment 200 c being identifiedby analytical data 162, content provider domain 130 may identify a newcontent delivery server different from content delivery server 121 d tostore content data 104. In some examples, in response to segment 200 cbeing identified by analytical data 162, content provider domain 130 mayidentify a content delivery server that may be located in a differentgeographical region from a location of content delivery server 121 d tostore content data 104.

In some examples, in response to segment 200 c being identified byanalytical data 162 as defective, content provider domain 130 mayidentify an infrastructure 302 at address 303, where infrastructure 302may be different from infrastructure 102. Content provider 130 mayrequest monitor domain 140 to deploy one or more monitor agents 152 toinfrastructure 302. Monitor agents 152 deployed to infrastructure 302may extract content data 104 from content delivery server 121 d usingresources of infrastructure 302, and may generate a new set of deliverydata 355. Monitor domain 140 may compare delivery data 355 with deliverydata 155, and based on the comparison, may generate a new set ofanalytical data 362. Analytical data 362 may identify one or moresegments 200 that may be defective. Content provider domain 130 maycompare analytical data 362 with analytical data 162 to determinewhether infrastructure 102 or infrastructure 302 should be used tofacilitate delivery of content data 104 to user domain 110. For example,if analytical data 162 identifies more defective segments thananalytical data 362, content provider domain 130 may determine to useinfrastructure 302 to facilitate delivery of content data 104 to userdomain 110.

In some examples, analytical data generator 160 may perform thecomparison of analytical data 362 and analytical data 162 and, inresponse, may generate a recommendation 370, and may send recommendation370 to content provider domain 130. Recommendation 370 may be dataeffective to indicate a recommendation based on an outcome of thecomparison of analytical data 162 and analytical data 362. For example,recommendation 370 may indicate a preference to select infrastructure302 over infrastructure 102. In some examples, recommendation 370 mayindicate whether to identify another content delivery server to storecontent data 104, replace a copy of content data 104 stored in contentdelivery domain 120, or make no changes, etc.

In some examples, monitor domain 140 may deploy more than one monitoragents 152 to one or more infrastructures. For example, monitor agent152 may be deployed to both infrastructure 102 and infrastructure 302.As a result of deploying monitor agent 152 to both infrastructures 102,302, monitor domain 140 may receive two sets of delivery data, such asdelivery data 155 and delivery data 355. Accordingly, analytical datagenerator 160 may generate recommendation 370 based on a comparison ofanalytical data 162 (based on delivery data 155) and analytical data 362(based on delivery data 355). Thus, monitor domain 140 may performanalysis associated with content delivery from different regions and/orinfrastructures.

In another example, monitor domain 140 may deploy different monitoragents (e.g., each monitor agent may simulate respective request, fromrespective user device, at respective address) to each infrastructure,and may generate different analytical data based on delivery datareceived from the different monitor agents. Thus, monitor domain 140 mayperform analysis based on simulations of user experience associated withdifferent user devices at different regions and/or infrastructures.

In another example, monitor domain 140 may deploy monitor agents to oneor more infrastructures, and may instruct each deployed monitor agent toextract content data 104 from two or more content delivery servers 121in content delivery domain 120 in order to perform analysis on contentdata being delivered from different content delivery servers.

In some examples, monitor agent 152 may be configured to extract contentdata associated with one or more versions of content 106 from contentdelivery domain 120. For example, monitor agent 152 may be configured toextract first content data associated with content 106 of ahigh-definition video mode, and may be configured to extract secondcontent data associated with content 106 of a ultra high-definitionvideo mode. Parameter processors 220 may generate respective sets ofparameter data for the first content data and the second content data.Monitor processor 142 may generate respective performance data for thefirst content data. Analytical data generator 160 may generate firstanalytical data that corresponds to the first content data, and maygenerate second analytical data that corresponds to the second contentdata. Analytical data generator 160 may send the first and secondanalytical data to content provider domain 130. Content provider domain130 may compare the first analytical data with the second analyticaldata to determine whether adjustments, such as whether to continueoffering content 106 of ultra high-definition video mode, may benecessary. In another example, monitor agent 152 may be configured toinclude target aspects of monitor domain 140.

Among other benefits, a system in accordance with this disclosure mayprovide a platform for content providers to determine whetheradjustments are needed to improve customer experience with contentdelivery. A system in accordance with this disclosure may also allowagents to be deployed in a cloud computing platform to extract contentdata for analysis, rather than seeking permission from users in order toinstall monitoring applications on user devices. A system in accordancewith this disclosure may also eliminate a need to embed monitoring intothe applications delivered to a user in order to track the user'sexperience. A system in accordance with this disclosure may also provideflexibility to content providers by providing a platform that may obtainanalytical data from a wide range of sample sizes. For example, hundredsof monitor agents may be deployed (or tens of monitor agents may bedeployed multiple times) to a cloud computing platform to monitorcontent delivery, instead of waiting for hundreds of user devices toactivate in order to analyze usage of the activated user devices.Further, content providers may specify particular content to analyze,instead of waiting for a significant amount of users to view theparticular content in order to perform analysis.

FIG. 4 illustrates a flow diagram for an example process to implement acontent delivery monitor, arranged in accordance with at least someembodiments described herein. The process in FIG. 4 could be implementedusing, for example, system 100 discussed above. An example process mayinclude one or more operations, actions, or functions as illustrated byone or more of blocks S2, S4, S6, S8, S10, S12, and/or S14. Althoughillustrated as discrete blocks, various blocks may be divided intoadditional blocks, combined into fewer blocks, or eliminated, dependingon the desired implementation.

Processing may begin at block S2 “Generate, by an agent generator of amonitor domain, a monitor agent that is effective to generate a firstrequest from a first address, wherein the first request is for thecontent data, and the first request is a simulation of a second requestfrom a second address in a user domain.” At block S2, an agent generatorof a monitor domain may generate a monitor agent. The monitor agent maybe effective to generate a first request from a first address. The firstrequest may be for the content data. The first request may be asimulation of a second request from a second address in a user domain.

Processing may continue from block S2 to block S4 “Deploy, by a monitorprocessor of the monitor domain, the monitor agent to the first address,wherein the monitor agent is effective to extract the content data froma content delivery domain to the first address, the monitor agent iseffective to generate delivery data associated with the content data,and the delivery data includes data associated with a delivery of thecontent data from the content delivery domain to the monitor agent atthe first address.” At block S4, a monitor processor may deploy themonitor agent to the first address. The monitor agent may be effectiveto extract the content data from a content delivery domain to the firstaddress. The monitor agent may be effective to generate delivery dataassociated with the content data. The delivery data may include dataassociated with a delivery of the content data from the content deliverydomain to the monitor agent at the first address.

Processing may continue from block S4 to block S6 “Receive, by acontroller of the monitor domain, the delivery data from the monitoragent.” At block S6, a controller of the monitor domain may receive thethe delivery data from the monitor agent.

Processing may continue from block S6 to block S8 “Distribute, by thecontroller, the delivery data to a parameter processor of the monitordomain.” At block S8, the controller may distribute the delivery data toa parameter processor of the monitor domain.

Processing may continue from block S8 to block S10 “Generate, by theparameter processor, parameter data, wherein the parameter data iseffective to indicate a parameter level associated with a parameter ofthe content data.” At block S10, the parameter processor may generateparameter data. The parameter data may be effective to indicate aparameter level associated with a parameter of the content data.

Processing may continue from block S10 to block S12 “Generate, by amonitor processor of the monitor domain, performance data based on theparameter data, wherein the performance data is effective to indicate anumber of defects among the content data.” At block S12, a monitorprocessor may generate performance data based on the parameter data. Theperformance data may be effective to indicate a number of defects amongthe content data.

Processing may continue from block S12 to block S14 “Identify, by ananalytical data generator of the monitor domain and based on theperformance data, a number of defective segments among the contentdata.” At block S14, an analytical data generator of the monitor domainmay identify a number of defective segments among the content data. Theidentification may be based on a number of defective segments among thecontent data.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims.

What is claimed is:
 1. A method for identifying defective segments ofcontent data associated with a piece of content, the method comprising:generating, by an agent generator of a monitor domain, a monitor agentthat is effective to generate a first request from a first address,wherein the first request is for the content data, and the first requestis a simulation of a second request from a second address in a userdomain; deploying, by a monitor processor of the monitor domain, themonitor agent to the first address, wherein the monitor agent iseffective to extract the content data from a content delivery domain tothe first address, the monitor agent is effective to generate deliverydata associated with the content data, and the delivery data includesdata associated with a delivery of the content data from the contentdelivery domain to the monitor agent at the first address; receiving, bya controller of the monitor domain, the delivery data from the monitoragent; distributing, by the controller, the delivery data to a parameterprocessor of the monitor domain; generating, by the parameter processor,parameter data, wherein the parameter data is effective to indicate aparameter level associated with a parameter of the content data;generating, by a monitor processor of the monitor domain, performancedata based on the parameter data, wherein the performance data iseffective to indicate a number of defects among the content data; andidentifying, by an analytical data generator of the monitor domain andbased on the performance data, a number of defective segments among thecontent data.
 2. The method of claim 1, wherein the monitor agent isfurther effective to extract the content data from the content deliverydomain based on a content retrieval protocol.
 3. The method of claim 1,wherein generating the parameter data comprises: outputting, by theparameter processor, the content data; and comparing, by the parameterprocessor, the output of the content data with a threshold associatedwith the parameter.
 4. The method of claim 1, wherein generating theperformance data comprises determining, by the parameter processor, thenumber of defects associated with one or more segments of the contentdata.
 5. The method of claim 1, wherein identifying the number ofdefective segments among the content data comprises: comparing, by theanalytical data generator, the number of parameter defects with athreshold, wherein the number of defects is associated with a particularsegment of the content data; and in response to the number of defectsbeing greater than the threshold, identifying the particular segment asa defective segment.
 6. The method of claim 1, further comprising,generating, by the analytical data generator of the monitor domain,analytical data based on the performance data, wherein the analyticaldata is effective to indicate the identified defective segments amongthe content data.
 7. The method of claim 6, further comprising sending,by the analytical data generator, the analytical data to a contentprovider domain.
 8. A system effective to identify defective segments ofcontent data associated with a piece of content, the system comprising:a memory; an agent generator configured to be in communication with thememory; a monitor processor configured to be in communication with theagent generator and the memory; a controller configured to be incommunication with the monitor processor; a parameter processorconfigured to be in communication with the controller and the monitorprocessor; an analytical data generator configured to be incommunication with the monitor processor; the agent generator beingconfigured to generate a monitor agent that is effective to generate afirst request from a first address, wherein the first request is for thecontent data, and the first request is a simulation of a second requestfrom a second address in a user domain; the monitor processor beingconfigured to deploy the monitor agent to the first address, wherein themonitor agent is effective to extract the content data from a contentdelivery domain, the monitor agent is effective to generate deliverydata associated with the content data, and the delivery data includesdata associated with a delivery of the content data from the contentdelivery domain to the monitor agent at the first address; thecontroller being configured to: receive the delivery data from themonitor agent; and distribute the delivery data to the parameterprocessor; the parameter processor being configured to: generateparameter data, wherein the parameter data is effective to indicate aparameter level associated with a parameter of the content data; andsend the parameter data to the monitor processor; the monitor processorbeing further configured to: generate performance data based on theparameter data, wherein the performance data is effective to indicate anumber of defects among the content data; send the performance data tothe analytical data generator; the analytical data generator beingconfigured to, based on the performance data, identify a number ofdefective segments among the content data.
 9. The system of claim 8,wherein the monitor agent is further effective to extract the contentdata from the content delivery domain based on a content retrievalprotocol stored in the memory.
 10. The system of claim 8, wherein theparameter processor is further configured to: output the content data;and compare the output of the content data with a threshold associatedwith the parameter to generate the parameter data.
 11. The system ofclaim 8, wherein the memory is configured to store the content data, andthe parameter processor is further configured to: output one or moresegments of the content data; and compare the output of the one or moresegments with the content data stored in the memory to generate theparameter data.
 12. The system of claim 8, wherein the monitor processoris further configured to: determining the number of defects associatedwith one or more segments of the content data; and generate theperformance data based on the determined number of defects associatedwith the one or more segments of the content data.
 13. The system ofclaim 8, wherein the analytical data generator is further configured to:compare the number of defects associated with a segment of the contentdata with a threshold, wherein the number of defects is associated witha particular segment of the content data; and in response to the numberof defects being greater than the threshold, identify the particularsegment as a defective segment.
 14. The system of claim 8, wherein theanalytical data generator is further configured to generate analyticaldata based on the performance data, the analytical data is effective toindicate the identified defective segments among the content data. 15.The system of claim 8, wherein the analytical data generator is furtherconfigured to send the analytical data to a content provider domain. 16.A system effective to evaluate a delivery of content data from a contentdelivery domain to a user domain, the system comprising: a memoryconfigured to store the content data; a content provider processorconfigured to be in communication with the memory, the content providerprocessor being configured to distribute a copy of the content data to acontent delivery domain; an agent generator configured to be incommunication with the memory; a monitor processor configured to be incommunication with the agent generator and the memory; a controllerconfigured to be in communication with the monitor processor; aparameter processor configured to be in communication with thecontroller and the monitor processor; an analytical data generatorconfigured to be in communication with the monitor processor; the agentgenerator being configured to generate a monitor agent that is effectiveto generate a first request from a first address, wherein the firstaddress is for the content data distributed to the content deliverydomain, and the first request is a simulation of a second request asecond address in a user domain; the monitor processor being configuredto deploy the monitor agent to a second address, wherein the monitoragent is effective to extract the content data from the content deliverydomain, and monitor agent is effective to generate delivery dataassociated with the content data distributed from the content deliverydomain, and the delivery data includes data associated with a deliveryof the content data from the content delivery domain to the monitoragent at the first address; the controller being configured to: receivethe delivery data from the monitor agent; and distribute the deliverydata to the parameter processor; the parameter processor beingconfigured to: generate parameter data, wherein the parameter data iseffective to indicate a parameter level associated with a parameter ofthe content data; and send the parameter data to the monitor processor;the monitor processor being further configured to: generate performancedata based on the parameter data, wherein the performance data iseffective to indicate a number of defects among the content data; sendthe performance data to the analytical data generator; the analyticaldata generator being configured to: based on the performance data,identify a number of defective segments among the content data, whereina presence of defective segments among content data is effective toindicate an efficiency of the delivery of the content data from thecontent delivery domain to the user domain; generate analytical databased on the performance data, the analytical data is effective toindicate the identified defective segments among the content data; andevaluate the delivery of the content data from the content deliverydomain to the user domain based on the analytical data.
 17. The systemof claim 16, wherein the monitor agent is further effective to extractthe content data from the content delivery domain based on a contentretrieval protocol stored in the memory.
 18. The system of claim 16,wherein the monitor processor is further configured to: determining thenumber of defects associated with one or more segments of the contentdata; and generate the performance data based on the determined numberof defects associated with the one or more segments of the content data.19. The system of claim 16, wherein the analytical data generator isfurther configured to: compare the number of defects associated with asegment of the content data with a threshold, wherein the number ofdefects is associated with a particular segment of the content data; andin response to the number of defects being greater than the threshold,identify the particular segment as a defective segment.
 20. The systemof claim 16, wherein the memory is configured to store the content data,and the parameter processor is further configured to: output the contentdata; and compare the output of the one or more segments with thecontent data stored in the memory to generate the parameter data.